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docs

Design and math references for the Vinv monorepo. These explain how the pipeline reasons — the engines themselves are documented in each package's own README.md.

Document What it covers Who it's for
learning.md The reward, propensity, and gating math that actually ships — every claim carries a file:line reference, plus measured off-policy results on this repo's own telemetry. Start here. Anyone who wants to understand how Vinv learns from episodes.
optimization-ontology.md The concept graph behind the optimization loop (detection → board → dispatch → verdict → learning): every node is a real on-disk artifact with its writers, readers, and expiry rule. Contributors working on the optimization pipeline, or agents walking a repo's optimization state.
testing-ontology.md The concept graph behind behavioral testing: what artifacts must exist, what produces each, and the top-to-bottom walk order — framework-agnostic. Contributors working on exerciser/identification, or agents reasoning about test coverage.

learning.md is the entry point; the two ontology documents are walkable maps of the on-disk artifacts each loop reads and writes.


part of vinv · vinv.ai